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Journal articles on the topic 'Taguchi's algorithm'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Marlan, Zulkifli Marlah, Khairur Rijal Jamaludin, Faizir Ramlie, and Nolia Harudin. "Taguchi's T-method with nearest integer-based binary bat algorithm for prediction." Bulletin of Electrical Engineering and Informatics 11, no. 4 (2022): 2215–24. http://dx.doi.org/10.11591/eei.v11i4.3859.

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Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat opti

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2

Zaharis, Zaharias D. "A MODIFIED TAGUCHI'S OPTIMIZATION ALGORITHM FOR BEAMFORMING APPLICATIONS." Progress In Electromagnetics Research 127 (2012): 553–69. http://dx.doi.org/10.2528/pier12040108.

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3

Chow Yong Huan, Wan Zuki Azman Wan Muhamad, Zainor Ridzuan Yahya, Nor Hizamiyani Abdul Azziz, Tan Li Mei, and Tan Xiao Jian. "Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset." Journal of Advanced Research in Applied Sciences and Engineering Technology 31, no. 3 (2023): 93–105. http://dx.doi.org/10.37934/araset.31.3.93105.

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The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisati

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4

Srivani Reddy. "Minimizing Localization error in Wireless sensor networks Taguchi method." Journal of Electrical Systems 20, no. 3 (2024): 4021–29. http://dx.doi.org/10.52783/jes.5407.

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Localization is a key research area in wireless sensor networks. The study focuses on the system's behavioral analysis in terms of minimizing localization error by adjusting parameters such as nodes, network size, communication range, and network deployment. Implementing the Kalman filter in the localization algorithm helps strengthen the technique and improve the success rate in the presence of measurement malfunctions. A series of trials were carried out to an optimal level utilizing the Taguchi technique to determine the most influential parameter among them. Taguchi's experimental research

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Moorthy, S. Srinivasa, K. Manonmani, and T. Elangovan. "An Optimization Approach to the Dry Sliding Wear Behavior of Particulate Filled Glass Fiber Reinforced Hybrid Composites." Journal of Engineered Fibers and Fabrics 10, no. 2 (2015): 155892501501000. http://dx.doi.org/10.1177/155892501501000213.

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The new set of hybrid composites consisting of randomly oriented short e glass fiber reinforcement, polyester resin and titanium oxide (TiO2) particulate were developed by hand layup technique. Wear test was carried out by rubber wheel abrasive test (RWAT) rig with the four operating variables filler content, applied load, abrasive grit size (Al2O3) and test duration. The wear test of the composites were done on the basis of Taguchi's L9 (34) Orthogonal array. Analysis of variance and S/N ratio was used to study the optimum wear. From, Taguchi's experimental design a mathematical regression mo

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Tang, Cheng-Yuan, Yi-Leh Wu, and Chien-Chin Peng. "Fundamental matrix estimation by multiobjective genetic algorithm with Taguchi's method." Applied Soft Computing 12, no. 1 (2012): 553–58. http://dx.doi.org/10.1016/j.asoc.2011.08.004.

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7

Ullah, Wasif, Mohd Fadzil Faisae Ab. Rashid, Muhammad Ammar Nik Mu’tasim, and Ghanshyam G. Tejani. "Minimizing Total Production Cost in Hybrid Flow Shop Scheduling using Taguchi Enhanced Particle Swarm Optimization Algorithm." Journal of Advanced Research Design 132, no. 1 (2025): 41–51. https://doi.org/10.37934/ard.132.1.4151.

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This study uses metaheuristic optimization algorithms to minimize the total production cost (TPC) in a hybrid flow shop scheduling (HFS) environment. Scheduling jobs in manufacturing systems is vital for fulfilling customer demands and improving efficiency. In this research, four well-established metaheuristic algorithms, namely Tuned Particle Swarm Optimization (TPSO), Standard particle swarm optimization (PSO), Sine cosine algorithm (SCA) and Arithmetic optimization algorithm (AOA), were explored for TPC optimization in HFS using MATLAB (2022b). Through experimental analysis, TPSO consistent

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8

Madhesan, Pradeep Kumar, Venkatesan Rajamanickam, and Manimurugan Manickam. "Optimization of process parameters in turning of magnesium AZ91D alloy for better surface finish using genetic algorithm." Acta Innovations, no. 43 (June 20, 2022): 54–62. http://dx.doi.org/10.32933/actainnovations.43.5.

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This research examined at the optimum cutting parameters for producing minimum surface roughness and maximum Material Removal Rate (MRR) when turning magnesium alloy AZ91D. Cutting speed (m/min), feed (mm/rev), and cut depth (mm) have all been considered in the experimental study. To find the best cutting parameters, Taguchi's technique and Response Surface Methodology (RSM), an evolutionary optimization techniques Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed. GA gives better results of 34.04% lesser surface roughness and 15.2% higher MRR values

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9

Yıldız, Ali Rıza. "A new design optimization framework based on immune algorithm and Taguchi's method." Computers in Industry 60, no. 8 (2009): 613–20. http://dx.doi.org/10.1016/j.compind.2009.05.016.

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10

Manogaran, Gnanasekaran, and Satheesh Anbalagan. "Investigation of turbulence characteristics and its influential parametric optimization of a double-sided lid-driven cavity using Taguchi and ANOVA methods." Thermal Science, no. 00 (2024): 56. http://dx.doi.org/10.2298/tsci230910056m.

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This paper investigates turbulence characteristics and the parameters controlling the turbulent incompressible flow of a double-sided lid-driven cavity. The effects of varying Reynolds numbers (1?104 ? Re ? 2?105), speed ratios (0.05 ? S ? 1.0), and aspect ratios (0.5 ? K ? 2.0) on the turbulent quantities, such as kinetic energy (k), dissipation (?), turbulent viscosity (?t) are analyzed. The k-? turbulence model equations are solved using the FVM-based SIMPLE algorithm. Taguchi's approach uses an L16 orthogonal array to determine the optimal cavity parameters. The significance of the conside

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11

Boukenoui, Rachid, Rafik Bradai, and Aissa Kheldoun. "A Taguchi method-based optimization algorithm for the analysis of the wind driven-self-excited induction generator." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 2 (2024): 769–83. https://doi.org/10.11591/ijpeds.v15.i2.pp769-783.

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This paper investigates the use of a new global optimization algorithm that is based on Taguchi method to determine the performance parameters of self-excited induction generator being driven by variable speed wind. This analysis is based on solving equations obtained from the per-phase equivalent circuit of the induction generator. The equations have two unknowns namely the frequency and the magnetizing reactance. Both unknown are strongly dependent on the wind turbine speed, the capacity of the excitation, the load being connected at the terminals of the stator and eventually the per-phase e

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12

Karen, İ., A. R. Yildiz, N. Kaya, N. Öztürk, and F. Öztürk. "Hybrid approach for genetic algorithm and Taguchi's method based design optimization in the automotive industry." International Journal of Production Research 44, no. 22 (2006): 4897–914. http://dx.doi.org/10.1080/00207540600619932.

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13

van, Canh, Nghien Ba, Dung Tien, Que van, Truong Xuan, and Duong Thuy. "Using support vector regression and non-dominated sorting genetic algorithm in multi-objective optimization of milling of S50C steel under MQL condition." Journal of Applied Engineering Science 20, no. 1 (2022): 123–30. http://dx.doi.org/10.5937/jaes0-31366.

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The modern machining industry faces reducing manufacturing cost pressure and improve product quality expectations. Due to this competition a manufacturer must continually identify cost cutting opportunities in manufacturing process. The keys technology represents cost-saving opportunities associated with reducing cutting fluid consumption, cutting energy consumption, and improves the overall performance of machining operations at the same time. Hence, multiple response optimization techniques have recently become the focus of research to improve product quality by increasing surface quality an

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Sheng, Nan, Cheng Liao, Wenbin Lin, Lei Chang, Qinghong Zhang, and Haijing Zhou. "A HYBRID OPTIMIZED ALGORITHM BASED ON EGO AND TAGUCHI'S METHOD FOR SOLVING EXPENSIVE EVALUATION PROBLEMS OF ANTENNA DESIGN." Progress In Electromagnetics Research C 17 (2010): 181–92. http://dx.doi.org/10.2528/pierc10091303.

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15

Hussian*, Syed Altaf, Palani Kumar K., and Md Alamgir. "Optimization of Specific Energy Consumption in Turning of GFRP Composites using Particle Swarm Optimization." Regular issue 10, no. 7 (2021): 11–17. http://dx.doi.org/10.35940/ijitee.g8890.0510721.

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In this paper, an attempt is made to optimize the control parameters for the minimization of specific energy consumption in turning GFRP composites using particle swarm optimization (PSO).Optimization of specific energy consumption in machining is helpful to evaluate the process energy characteristics and also facilitates choosing the best control parameters for energy saving. The control parameters considered are cutting speed, feed, depth of cut and fiber orientation angle. Experiments are planned and executed according to Taguchi's L25 orthogonal array in the design of experiments on an all

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Shunmugam, M. S., and N. Siva Prasad. "Prediction of stress in fillet portion of spur gears using artificial neural networks." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 22, no. 1 (2007): 41–51. http://dx.doi.org/10.1017/s0890060408000036.

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AbstractA fillet curve is provided at the root of the spur gear tooth, as stresses are high in this portion. The fillet curve may be a trochoid or an arc of suitable size as specified by designer. The fillet stress is influenced by the fillet geometry as well as the number of teeth, modules, and the pressure angle of the gear. Because the relationship is nonlinear and complex, an artificial neural network and a backpropagation algorithm are used in the present work to predict the fillet stresses. Training data are obtained from finite element simulations that are greatly reduced using Taguchi'

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Singh, Abhishek, Rajiv Kumar Garg, and Anish Sachdeva. "An Extensive Review of Various Optimization Techniques for Electric Discharge Machining." Prabha Materials Science Letters 3, no. 1 (2024): 123–45. http://dx.doi.org/10.33889/pmsl.2024.3.1.009.

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In this paper, an investigation of wire and electric discharge machining has been provided. Wider possibilities for the creation of composites and sophisticated materials were made possible by advances in machining science. As research in this area continues, more materials with complicated meteorological structures and strong mechanical resistance capabilities are emerging. Because of the exceptional strength, toughness, and hardness of these materials, advanced machining techniques are replacing traditional machining techniques in this industry. One unique type of advanced machining techniqu

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18

Kumar, P. N. Ram, Anjana Viswanath, and R. Sridharan. "Hybrid genetic algorithm for multi-objective flow shop scheduling problem with sequence dependent setup time: parameter design using Taguchi's robust design method." International Journal of Process Management and Benchmarking 9, no. 4 (2019): 419. http://dx.doi.org/10.1504/ijpmb.2019.10025107.

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Viswanath, Anjana, R. Sridharan, and P. N. Ram Kumar. "Hybrid genetic algorithm for multi-objective flow shop scheduling problem with sequence dependent setup time: parameter design using Taguchi's robust design method." International Journal of Process Management and Benchmarking 9, no. 4 (2019): 419. http://dx.doi.org/10.1504/ijpmb.2019.103415.

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20

Marlah Marlan, Zulkifli, Faizir Ramlie, Khairur Rijal Jamaludin, and Nolia Harudin. "Enhanced Taguchi’s T-method using angle modulated Bat algorithm for prediction." Bulletin of Electrical Engineering and Informatics 11, no. 5 (2022): 2828–35. http://dx.doi.org/10.11591/eei.v11i5.4350.

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Analysis of multivariate historical information in predicting future state or unknown outcomes is the core function of Taguchi’s T-method. Introduced by Dr. Genichi Taguchi under Mahalanobis-Taguchi system, the T-method combines regression principle and robust quality engineering element in formulating a predictive model and employs taguchi’s orthogonal array design in optimizing the model through feature or variable selection process. There is a concern regarding the sub-optimality of the T-method prediction accuracy, particularly when the orthogonal array failed to offer a significant number

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21

Pan, Lung-Fa, Yi-Hua Chen, Chun-Chieh Wang, Bing-Ru Peng, Samrit Kittipayak, and Lung-Kwang Pan. "Optimizing cardiac CT angiography minimum detectable difference via Taguchi’s dynamic algorithm, a V-shaped line gauge, and three PMMA phantoms." Technology and Health Care 30 (February 25, 2022): 91–103. http://dx.doi.org/10.3233/thc-228009.

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BACKGROUND: Radiologists widely use the minimum detectable difference (MDD) concept for inspecting the imaging quality and quantify the spatial resolution of scans. OBJECTIVE: This study adopted Taguchi’s dynamic algorithm to optimize the MDD of cardiac CT angiography (CTA) using a V-shaped line gauge and three PMMA phantoms (50, 70, and 90 kg). METHODS: The phantoms were customized in compliance with the ICRU-48 report, whereas the V-shaped line gauge was indigenous to solidify the cardiac CTA scan image quality by two adjacent peaks along the V-shaped slit. Accordingly, the six factors A-F a

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22

Sahoo, Shubhashree, Rabindra Dalei, Subhendu Rath, Uttam Sahu, and Krishneshwar Tiwary. "Parameter Optimization of Genetic Algorithm Utilizing Taguchi Design for Gliding Trajectory Optimization of Missile." Defence Science Journal 74, no. 01 (2023): 127–42. http://dx.doi.org/10.14429/dsj.74.18496.

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The present study aims to establish a genetic algorithm (GA) method to optimize gliding trajectory of a missile. The trajectory is optimized by discretizing the angle of attack (AOA) and solving optimal control problem to achieve maximum gliding range. GA is employed to resolve the optimal control problem to achieve optimized AOA. A Taguchi’s design of experiments was proposed contrary to full factorial method to ascertain the GA parameters. The experiments have been designed as per Taguchi’s design of experiments using L27 orthogonal array. Systematic reasoning ability of Taguchi method is ex

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Mohammed, Tarawneh* P.V.Rajendra Sethupathi P.Senthil. "PARAMETRIC OPTIMIZATION FOR IMPROVING THE PERFORMANCE OF SINGLE SLOPE SOLAR STILL THROUGH EXPERIMENTAL STUDIES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 9 (2016): 291–99. https://doi.org/10.5281/zenodo.154192.

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An attempt is made to improve the performance of single slope solar still for the production of fresh water in this study. The prime aim is to experimentally investigate the influence of control factors namely stone quantity, sea water level and double glazing on the yield of the solar still. Nine experiments were conducted based on Taguchi’s orthogonal array. It is noted that double glazing effect makes substantial improvement in the yield of solar still. A non-linear regression model is also developed for the process. The optimum parametric conditions are found through the Taguchi method and

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Saber, WesamEldin I. A., Abdulaziz A. Al-Askar, and Khalid M. Ghoneem. "Exclusive Biosynthesis of Pullulan Using Taguchi’s Approach and Decision Tree Learning Algorithm by a Novel Endophytic Aureobasidium pullulans Strain." Polymers 15, no. 6 (2023): 1419. http://dx.doi.org/10.3390/polym15061419.

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Pullulan is a biodegradable, renewable, and environmentally friendly hydrogel biopolymer, with potential uses in food, medicine, and cosmetics. New endophytic Aureobasidium pullulans (accession number; OP924554) was used for the biosynthesis of pullulan. Innovatively, the fermentation process was optimized using both Taguchi’s approach and the decision tree learning algorithm for the determination of important variables for pullulan biosynthesis. The relative importance of the seven tested variables that were obtained by Taguchi and the decision tree model was accurate and followed each other’

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Ashok, R., L. Poovazhagan, S. Srinath Ramkumar, and S. Vignesh Kumar. "Optimization of Material Removal Rate in Wire-EDM Using Fuzzy Logic and Artifical Neural Network." Applied Mechanics and Materials 867 (July 2017): 73–80. http://dx.doi.org/10.4028/www.scientific.net/amm.867.73.

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Present work aims to develop a model and optimize the material removal rate (MRR) in complex wire electric discharge machining (EDM) process. Initially various percentages of aluminium alloy hybrid Nanocomposites were fabricated by novel ultrasonication method. The sample specimens were cut and machined using wire EDM. Experiments were carried out using Taguchi’s L18 orthogonal array under different cutting parameters like Pulse-on, Pulse- off, current and servo voltage. Fuzzy-based Taguchi method and artificial neural network (ANN) with back propagation algorithm were used to optimize the mat

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Umanath, K., and D. Devika. "Optimization of electric discharge machining parameters on titanium alloy (ti-6al-4v) using Taguchi parametric design and genetic algorithm." MATEC Web of Conferences 172 (2018): 04007. http://dx.doi.org/10.1051/matecconf/201817204007.

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The aim of this research work is to analyze the significant of process variables and find the optimum process variables in electric discharge machining (EDM) of Titanium alloy (Ti-6Al-4V) .The variables considered are peak current, pulse-on-time and pulse-off-time where as the responses are Material Removal Rate(MRR) and Surface Roughness(SR). MITSUBISHI EA8 spark erosion machine is employed for this work and copper tungsten electrode of ∅14 mm is used in experimental trials. The experimental runs are done based on Taguchi L27 orthogonal array. The signal-to-noise ratio, the analysis of varian

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Shou, Ho Nien. "The Study on Robust Controller Synthesis Using Genetic Optimization Algorithm Integrating Taguchi Methods." Applied Mechanics and Materials 284-287 (January 2013): 2341–45. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2341.

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A controller synthesis algorithm is developed in this paper. The algorithm employs the genetic algorithm for parameter optimization and Taguchi method for the planning of trails in applying the genetic algorithms. The resulting two-phase algorithm explores the orthogonal array in Taguchi method to conduct a series of experiments so that key parameters pertaining to the control factors, noise factors, and quality factors can be determined. In the first phase, a matrix-type experiment is conducted to determine the configuration for parameter optimization. The second phase then applies parameter

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Kuntoğlu, Mustafa, Osman Acar, Munish Kumar Gupta, et al. "Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140." Machines 9, no. 5 (2021): 90. http://dx.doi.org/10.3390/machines9050090.

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The present paper deals with the optimization of the three components of cutting forces and the Material Removal Rate (MRR) in the turning of AISI 5140 steel. The Harmonic Artificial Bee Colony Algorithm (H-ABC), which is an improved nature-inspired method, was compared with the Harmonic Bee Algorithm (HBA) and popular methods such as Taguchi’s S/N ratio and the Response Surface Methodology (RSM) in order to achieve the optimum parameters in machining applications. The experiments were performed under dry cutting conditions using three cutting speeds, three feed rates, and two depths of cuts.

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El-Banna, Mahmoud. "Modified Mahalanobis Taguchi System for Imbalance Data Classification." Computational Intelligence and Neuroscience 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/5874896.

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The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB),

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Al-Zoubi, Asem S., Anas Atef Amaireh, and Nihad I. Dib. "Comparative and comprehensive study of linear antenna arrays’ synthesis." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2645. http://dx.doi.org/10.11591/ijece.v12i3.pp2645-2654.

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<span>In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; g

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Asem, S. Al-Zoubi, Atef Amaireh Anas, and I. Dib Nihad. "Comparative and comprehensive study of linear antenna arrays' synthesis." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2645–54. https://doi.org/10.11591/ijece.v12i3.pp2645-2654.

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In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; grasshopper o

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32

Jiang, Qingquan, Xiaoya Liao, Rui Zhang, and Qiaozhen Lin. "Energy-Saving Production Scheduling in a Single-Machine Manufacturing System by Improved Particle Swarm Optimization." Mathematical Problems in Engineering 2020 (November 5, 2020): 1–16. http://dx.doi.org/10.1155/2020/8870917.

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A single-machine scheduling problem that minimizes the total weighted tardiness with energy consumption constraints in the actual production environment is studied in this paper. Based on the properties of the problem, an improved particle swarm optimization (PSO) algorithm embedded with a local search strategy (PSO-LS) is designed to solve this problem. To evaluate the algorithm, some computational experiments are carried out using PSO-LS, basic PSO, and a genetic algorithm (GA). Before the comparison experiment, the Taguchi method is used to select appropriate parameter values for these thre

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Khorramizadeh, Mostafa, and Vahid Riahi. "A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/612604.

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The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.

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Ravipudi, Jaya Lakshmi. "Synthesis of Linear, Planar, and Concentric Circular Antenna Arrays Using Rao Algorithms." International Journal of Applied Evolutionary Computation 11, no. 3 (2020): 31–49. http://dx.doi.org/10.4018/ijaec.2020070103.

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The aim of this paper is to display the efficacy of three newly proposed optimization algorithms named as Rao-1, Rao-2, and Rao-3 in synthesizing antenna arrays. The algorithms are applied to three different antenna array configurations. Thinned arrays with isotropic radiators are considered and the main objective is to find the optimal configuration of ON/OFF elements that produce low side lobe levels. The results of Rao-1, Rao-2, and Rao-3 algorithms are compared with those of improved genetic algorithm (IGA), hybrid Taguchi binary particle swarm optimization (HTBPSO), teaching-learning-base

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Alshibli, Mohammad, Ahmed ElSayed, Elif Kongar, Tarek Sobh, and Surendra Gupta. "A Robust Robotic Disassembly Sequence Design Using Orthogonal Arrays and Task Allocation." Robotics 8, no. 1 (2019): 20. http://dx.doi.org/10.3390/robotics8010020.

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Disassembly sequence planning (DSP) is a nondeterministic polynomial time (NP) complete problem, making the utilization of metaheuristic approaches a viable alternative. DSP aims at creating efficient algorithms for deriving the optimum or near-optimum disassembly sequence for a given product or a product family. The problem-specific nature of such algorithms, however, requires these solutions to be validated, proving their versatility in accommodating substantial variations in the problem environment. To achieve this goal, this paper utilizes Taguchi’s orthogonal arrays to test the robustness

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Xu, Weixiang, Dongbao Jia, Zhaoman Zhong, Cunhua Li, and Zhongxun Xu. "Intelligent Dendritic Neural Model for Classification Problems." Symmetry 14, no. 1 (2021): 11. http://dx.doi.org/10.3390/sym14010011.

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In recent years, the dendritic neural model has been widely employed in various fields because of its simple structure and inexpensive cost. Traditional numerical optimization is ineffective for the parameter optimization problem of the dendritic neural model; it is easy to fall into local in the optimization process, resulting in poor performance of the model. This paper proposes an intelligent dendritic neural model firstly, which uses the intelligent optimization algorithm to optimize the model instead of the traditional dendritic neural model with a backpropagation algorithm. The experimen

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Bahrampour, Peyman, Seyyed Esmaeil Najafi, Farhad Hosseinzadeh lotfi, and Ahmad Edalatpanah. "Designing a Scenario-Based Fuzzy Model for Sustainable Closed-Loop Supply Chain Network considering Statistical Reliability: A New Hybrid Metaheuristic Algorithm." Complexity 2023 (April 21, 2023): 1–24. http://dx.doi.org/10.1155/2023/1337928.

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In this study, a new nonlinear mathematical programming model of mixed integer was presented to formulate the problem of designing a sustainable closed loop supply chain, in which the three aspects of sustainability, i.e., social effect such as job creation, customer satisfaction, and distributors, environmental effects such as reducing air pollution, and economic effects such as reducing supply chain costs, increasing supply chain reliability, quality of returned products by customers, and product routing were considered. In order to solve the proposed model, a new hybrid metaheuristic algori

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Boukenoui, Rachid, Rafik Bradai, and Aissa Kheldoun. "A Taguchi method-based optimization algorithm for the analysis of the wind driven-self-excited induction generator." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 2 (2024): 769. http://dx.doi.org/10.11591/ijpeds.v15.i2.pp769-783.

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This paper investigates the use of a new global optimization algorithm that is based on Taguchi method to determine the performance parameters of self-excited induction generator being driven by variable speed wind. This analysis is based on solving equations obtained from the per-phase equivalent circuit of the induction generator. The equations have two unknowns namely the frequency and the magnetizing reactance. Both unknown are strongly dependent on the wind turbine speed, the capacity of the excitation, the load being connected at the terminals of the stator and eventually the per-phase e

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Seifbarghy, Mehdi, and Seyed Shamsodin Hosseini. "A novel meta-heuristic algorithm for multi-objective dynamic facility layout problem." RAIRO - Operations Research 50, no. 4-5 (2016): 869–90. https://doi.org/10.1051/ro/2016057.

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This paper proposes an integrated approach for dynamic facility layout problem considering the material handling equipment (MHE). The objectives of this problem are minimization of the fixed costs of MHE, minimization of material handling cost (MHC) and minimization of machine rearrangement costs (MRC). To be more realistic, MHE fixed costs, MRC and MHC, which might be of different importance to decision maker, are considered separately in three objective functions. An integrated model is proposed which is able to simultaneously select the MHE along with the arranging and re-arranging faciliti

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Gabi, Danlami, Abdul Samad Ismail, Anazida Zainal, and Zalmiyah Zakaria. "Solving Task Scheduling Problem in Cloud Computing Environment Using Orthogonal Taguchi-Cat Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 3 (2017): 1489. http://dx.doi.org/10.11591/ijece.v7i3.pp1489-1497.

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In cloud computing datacenter, task execution delay is no longer accidental. In recent times, a number of artificial intelligence scheduling techniques are proposed and applied to reduce task execution delay. In this study, we proposed an algorithm called Orthogonal Taguchi Based-Cat Swarm Optimization (OTB-CSO) to minimize total task execution time. In our proposed algorithm Taguchi Orthogonal approach was incorporated at CSO tracing mode for best task mapping on VMs with minimum execution time. The proposed algorithm was implemented on CloudSim tool and evaluated based on makespan metric. Ex

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Wang, Kaiming, Wei Liu, Yuxiang Hong, et al. "An Overview of Technological Parameter Optimization in the Case of Laser Cladding." Coatings 13, no. 3 (2023): 496. http://dx.doi.org/10.3390/coatings13030496.

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This review examines the methods used to optimize the process parameters of laser cladding, including traditional optimization algorithms such as single-factor, regression analysis, response surface, and Taguchi, as well as intelligent system optimization algorithms such as neural network models, genetic algorithms, support vector machines, the new non-dominance ranking genetic algorithm II, and particle swarm algorithms. The advantages and disadvantages of various laser cladding process optimization methods are analyzed and summarized. Finally, the development trend of optimization methods in

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B.V., Dharmendra, Shyam Prasad Kodali, and Nageswara Rao Boggarapu. "Multi-objective optimization for optimum abrasive water jet machining process parameters of Inconel718 adopting the Taguchi approach." Multidiscipline Modeling in Materials and Structures 16, no. 2 (2019): 306–21. http://dx.doi.org/10.1108/mmms-10-2018-0175.

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Purpose The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness. Design/methodology/approach Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters. Findings Empirical relations are developed for MRR and

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Mukherjee, Rajarshi, Debkalpa Goswami, and Shankar Chakraborty. "Parametric Optimization of Nd:YAG Laser Beam Machining Process Using Artificial Bee Colony Algorithm." Journal of Industrial Engineering 2013 (July 31, 2013): 1–15. http://dx.doi.org/10.1155/2013/570250.

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Nd:YAG laser beam machining (LBM) process has a great potential to manufacture intricate shaped microproducts with its unique characteristics. In practical applications, such as drilling, grooving, cutting, or scribing, the optimal combination of Nd:YAG LBM process parameters needs to be sought out to provide the desired machining performance. Several mathematical techniques, like Taguchi method, desirability function, grey relational analysis, and genetic algorithm, have already been applied for parametric optimization of Nd:YAG LBM processes, but in most of the cases, suboptimal or near opti

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Song, Juan, Bangfu Wang, and Xiaohong Hao. "Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering." Materials 17, no. 16 (2024): 4093. http://dx.doi.org/10.3390/ma17164093.

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In modern manufacturing, optimization algorithms have become a key tool for improving the efficiency and quality of machining technology. As computing technology advances and artificial intelligence evolves, these algorithms are assuming an increasingly vital role in the parameter optimization of machining processes. Currently, the development of the response surface method, genetic algorithm, Taguchi method, and particle swarm optimization algorithm is relatively mature, and their applications in process parameter optimization are quite extensive. They are increasingly used as optimization ob

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Coban, Melih, and Suleyman Sungur Tezcan. "Feed-Forward Neural Networks Training with Hybrid Taguchi Vortex Search Algorithm for Transmission Line Fault Classification." Mathematics 10, no. 18 (2022): 3263. http://dx.doi.org/10.3390/math10183263.

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In this study, the hybrid Taguchi vortex search (HTVS) algorithm, which exhibits a rapid convergence rate and avoids local optima, is employed as a new training algorithm for feed-forward neural networks (FNNs) and its performance was analyzed by comparing it with the vortex search (VS) algorithm, the particle swarm optimization (PSO) algorithm, the gravitational search algorithm (GSA) and the hybrid PSOGSA algorithm. The HTVS-based FNN (FNNHTVS) algorithm was applied to three datasets (iris classification, wine recognition and seed classification) taken from the UCI database (the machine lear

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Radhakrishna, Laishetty, V. S. Hariharan, Banothu Srinivas, et al. "Performance Evaluation of ML-Based Algorithm and Taguchi Algorithm of the Hardness Value of the Friction Stir Welded AA6262 Joints at a Nugget Joint." E3S Web of Conferences 430 (2023): 01249. http://dx.doi.org/10.1051/e3sconf/202343001249.

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Nowadays, industry 4.0 plays a tremendous role in the manufacturing industries for increasing the amount of data and accuracy in modern manufacturing systems. Thanks to artificial intelligence, particularly machine learning, big data analytics have dramatically amended, and manufacturers easily exploit organized and unorganized data. This study utilized hybrid optimization algorithms to find friction stir welding and optimal hardness value at the nugget zone. A similar AA 6262 material was used and welded in a butt joint configuration. Tool rotational speed (RPM), tool traverse speed (mm/min),

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RAVEENDRAN, P., S. V. ALAGARSAMY, M. RAVICHANDRAN, and M. MEIGNANAMOORTHY. "EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH DECISION TREE ALGORITHM." Surface Review and Letters 28, no. 04 (2021): 2150021. http://dx.doi.org/10.1142/s0218625x21500219.

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The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed ([Formula: see text]), feed ([Formula: see text]), and depth of cut ([Formula: see text]) on surface roughness (Ra) of turning AA7075 filled with 10[Formula: see text]wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner withi

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Yousefikhoshbakht, Majid, Nasrin Malekzadeh, and Mohammad Sedighpour. "Solving the Traveling Salesman Problem Based on The Genetic Reactive Bone Route Algorithm whit Ant Colony System." International Journal of Production Management and Engineering 4, no. 2 (2016): 65. http://dx.doi.org/10.4995/ijpme.2016.4618.

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<p>The TSP is considered one of the most well-known combinatorial optimization tasks and researchers have paid so much attention to the TSP for many years. In this problem, a salesman starts to move from an arbitrary place called depot and after visits all of the nodes, finally comes back to the depot. The objective is to minimize the total distance traveled by the salesman. Because this problem is a non-deterministic polynomial (NP-hard) problem in nature, a hybrid meta-heuristic algorithm called REACSGA is used for solving the TSP. In REACSGA, a reactive bone route algorithm that uses

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Kim, Jinho, Chang Seob Kim, and Zong Woo Geem. "A Memetic Approach for Improving Minimum Cost of Economic Load Dispatch Problems." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/906028.

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Economic load dispatch problem is a popular optimization problem in electrical power system field, which has been so far tackled by various mathematical and metaheuristic approaches including Lagrangian relaxation, branch and bound method, genetic algorithm, tabu search, particle swarm optimization, harmony search, and Taguchi method. On top of these techniques, this study proposes a novel memetic algorithm scheme combining metaheuristic algorithm and gradient-based technique to find better solutions for an economic load dispatch problem with valve-point loading. Because metaheuristic algorith

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Ikedue, Meshach Chukwuebuka, John Rajan, Sunday Oke, Ebun Fasina, Babatunde Alade Sawyerr, and Wasiu Oyediran Adedeji. "Optimisation of Electrical Discharge Machining Processing for AZ91 Magnesium Alloy using Coupled AHP-Taguchi Analyses-GA Method with the Rank Selection Approach." Journal of Applied Science & Process Engineering 10, no. 2 (2023): 79–93. http://dx.doi.org/10.33736/jaspe.5162.2023.

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Despite being contemporary, the wire electrical discharge machining (EDM) industry is burdened with complicated and challenging problems. However, the double optimisation method involving Taguchi analyses and genetic algorithms is a powerful tool to help tackle some of these problems. This article evaluates the wire EDM process through a rank-based genetic algorithm coupled with the AHP-Taguchi analyses using the AZ91 magnesium alloy for the first time in the literature. The rank selection method was used at the selection stage of the operations. Six parameters, namely pulse on time, pulse off

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